Molecular recognition of an RNA trafficking element by heterogeneous nuclear ribonucleoprotein A2

Heterogeneous nuclear ribonucleoprotein (hnRNP) A2 is a multitasking protein involved in RNA packaging, alternative splicing of pre-mRNA. telomere maintenance, cytoplasmic RNA trafficking, and translation. It binds short segments of single-stranded nucleic acids, including the A2RE11 RNA element that is necessary and sufficient for cytoplasmic transport of a subset of rnRNAs in oligodendrocytes and neurons. We have explored the structures of hnRNP A2, its RNA recognition motifs (RRMs) and Gly-rich module, and the RRM complexes with A2RE11. Circular dichroism spectroscopy showed that the secondary structure of the first 189 residues of hnRNP A2 parallels that of the tandem beta alpha beta beta alpha beta RRMs of its paralogue, hnRNP A1, previously deduced from X-ray diffraction studies. The unusual GRD was shown to have substantial beta-sheet and beta-turn structure. Sedimentation equilibrium and circular dichroism results were consistent with the tandem RRM region being monomeric and supported earlier evidence for the binding of two A2RE11 oligoribonucleotides to this domain, in contrast to the protein dimer formed by the complex of hnRNP A1 with the telomeric ssDNA repeat. A three-dimensional structure for the N-terminal, two-RRM-containing segment of hnRNP A2 was derived by homology modeling. This structure was used to derive a model for the complex with A2RE11 using the previously described interaction of pairs of stacked nucleotides with aromatic residues on the RRM beta-sheet platforms, conserved in other RRM-RNA complexes, together with biochemical data and molecular dynamics-based observations of inter-RRM mobility.

Novel approach to tailoring molecular weight distribution and structure with a difunctional RAFT agent

This work has demonstrated that for the first time a single RAFT agent (i. e., difunctional) can be used in conjunction with a radical initiator to obtain a desired M-n and PDI with controlled rates of polymerization. Simulations were used not only to verify the model but also to provide us with a predictive tool to generate other MWDs. It was also shown that all the MWDs prepared in this work could be translated to higher molecular weights through chain extension experiments with little or no compromise in the control of end group functionality. The ratio of monofunctional to difunctional SdC(CH2Ph)S- end groups, XPX and XP (where X) S=C(CH2Ph) S-), can be controlled by simply changing the concentration of initiator, AIBN. Importantly, the amount of dead polymer is extremely low and fulfils the criterion as suggested by Szwarc (Nature 1956) that to meet living requirements nonfunctional polymeric species formed by side reactions in the process should be undetectable by analytical techniques. In addition, this novel methodology will allow the synthesis of AB, ABA, and statistical multiblock copolymers with predetermined ratios to be produced in a one-pot reaction.

Quantum atom optics with fermions from molecular dissociation

We study a fermionic atom optics counterpart of parametric down-conversion with photons. This can be realized through dissociation of a Bose-Einstein condensate of molecular dimers consisting of fermionic atoms. We present a theoretical model describing the quantum dynamics of dissociation and find analytic solutions for mode occupancies and atomic pair correlations, valid in the short time limit. The solutions are used to identify upper bounds for the correlation functions, which are applicable to any fermionic system and correspond to ideal particle number-difference squeezing.

Quantum entanglement in the two-impurity Kondo model

In order to quantify quantum entanglement in two-impurity Kondo systems, we calculate the concurrence, negativity, and von Neumann entropy. The entanglement of the two Kondo impurities is shown to be determined by two competing many-body effects, namely the Kondo effect and the Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction, I. Due to the spin-rotational invariance of the ground state, the concurrence and negativity are uniquely determined by the spin-spin correlation between the impurities. It is found that there exists a critical minimum value of the antiferromagnetic correlation between the impurity spins which is necessary for entanglement of the two impurity spins. The critical value is discussed in relation with the unstable fixed point in the two-impurity Kondo problem. Specifically, at the fixed point there is no entanglement between the impurity spins. Entanglement will only be created [and quantum information processing (QIP) will only be possible] if the RKKY interaction exchange energy, I, is at least several times larger than the Kondo temperature, T-K. Quantitative criteria for QIP are given in terms of the impurity spin-spin correlation.

The molecular basis of temperature compensation in the Arabidopsis circadian clock

Circadian clocks maintain robust and accurate timing over a broad range of physiological temperatures, a characteristic termed temperature compensation. In Arabidopsis thaliana, ambient temperature affects the rhythmic accumulation of transcripts encoding the clock components TIMING OF CAB EXPRESSION1 (TOC1), GIGANTEA (GI), and the partially redundant genes CIRCADIAN CLOCK ASSOCIATED1 (CCA1) and LATE ELONGATED HYPOCOTYL (LHY). The amplitude and peak levels increase for TOC1 and GI RNA rhythms as the temperature increases (from 17 to 27 degrees C), whereas they decrease for LHY. However, as temperatures decrease ( from 17 to 12 degrees C), CCA1 and LHY RNA rhythms increase in amplitude and peak expression level. At 27 degrees C, a dynamic balance between GI and LHY allows temperature compensation in wild-type plants, but circadian function is impaired in Ihy and gi mutant plants. However, at 12 degrees C, CCA1 has more effect on the buffering mechanism than LHY, as the cca1 and gi mutations impair circadian rhythms more than Ihy at the lower temperature. At 17 degrees C, GI is apparently dispensable for free-running circadian rhythms, although partial GI function can affect circadian period. Numerical simulations using the interlocking-loop model show that balancing LHY/CCA1 function against GI and other evening-expressed genes can largely account for temperature compensation in wild-type plants and the temperature-specific phenotypes of gi mutants.

Implementation of particle-scale rotation in the 3-d Lattice Solid Model

In this study, 3-D Lattice Solid Model (LSMearth or LSM) was extended by introducing particle-scale rotation. In the new model, for each 3-D particle, we introduce six degrees of freedom: Three for translational motion, and three for orientation. Six kinds of relative motions are permitted between two neighboring particles, and six interactions are transferred, i.e., radial, two shearing forces, twisting and two bending torques. By using quaternion algebra, relative rotation between two particles is decomposed into two sequence-independent rotations such that all interactions due to the relative motions between interactive rigid bodies can be uniquely decided. After incorporating this mechanism and introducing bond breaking under torsion and bending into the LSM, several tests on 2-D and 3-D rock failure under uni-axial compression are carried out. Compared with the simulations without the single particle rotational mechanism, the new simulation results match more closely experimental results of rock fracture and hence, are encouraging. Since more parameters are introduced, an approach for choosing the new parameters is presented.

Structure and dynamics of a gene network model incorporating small RNAs

As advances in molecular biology continue to reveal additional layers of complexity in gene regulation, computational models need to incorporate additional features to explore the implications of new theories and hypotheses. It has recently been suggested that eukaryotic organisms owe their phenotypic complexity and diversity to the exploitation of small RNAs as signalling molecules. Previous models of genetic systems are, for several reasons, inadequate to investigate this theory. In this study, we present an artificial genome model of genetic regulatory networks based upon previous work by Torsten Reil, and demonstrate how this model generates networks with biologically plausible structural and dynamic properties. We also extend the model to explore the implications of incorporating regulation by small RNA molecules in a gene network. We demonstrate how, using these signals, highly connected networks can display dynamics that are more stable than expected given their level of connectivity.

Molecular characterization of three gonad cell lines

To facilitate the study of the regulation and downstream interactions of genes involved in gonad development it is important to have a suitable cell culture model. We therefore aimed to characterize molecularly three different mouse gonad cell lines. TM3 and TM4 cells were originally isolated from prepubertal mouse gonads and were tentatively identified as being of Leydig cell and Sertoli cell origin, respectively, based upon their morphology and hormonal responses. The third line is a conditionally immortalized cell line, derived from 10.5-11.5 days post-coitum (dpc) male gonads of transgenic embryos carrying a temperature-sensitive SV40 large T-antigen. We studied by reverse transcription-polymerase chain reaction (RT-PCR) the expression profiles of a number of genes known to be important for early gonad development. Moreover, we assessed these cell lines for their capacity to induce Sox9 transcription upon expression of Sry, a key molecular event occurring during sex determination. We found that all three cell lines were unable to upregulate Sox9 expression upon transfection of Sry-expression constructs, even though these cells express many of the studied embryonic gonad genes. These observations point to a requirement for SRY cofactors for direct or indirect upregulation of Sox9 expression during testis determination. Copyright © 2003 S. Karger AG, Basel

Monitoring inflammation and airway remodeling by FMT in a chronic asthma model

Asthma is a multifactorial disease for which a variety of mouse models have been developed. A major drawback of these models is represented by the transient nature of the airway pathology peaking 24 to 72 hours after challenge and resolving in 1 to 2 weeks. The objective of this study is to characterize the temporal evolution of pulmonary inflammation and remodeling in a recently described mouse model of chronic asthma (8 week treatment with 3 allergens relevant for the human pathology: Dust mite, Ragweed, and Aspergillus; DRA). We studied the DRA model taking advantage of fluorescence molecular tomography (FMT) imaging using near-infrared probes to non-invasively evaluate lung inflammation and airway remodeling. At 4, 6, 8 or 11 weeks, cathepsin- and metalloproteinase-dependent fluorescence was evaluated in vivo. A subgroup of animals, after 4 weeks of DRA, was treated with Budesonide (100 µg/kg intranasally) daily for 4 weeks. Cathepsin-dependent fluorescence in DRA-sensitized mice resulted significantly increased at 6 and 8 weeks, and was markedly inhibited by budesonide. This fluorescent signal well correlated with ex vivo analysis such as bronchoalveolar lavage eosinophils and alveolar cell infiltration. Metalloproteinase-dependent fluorescence was significantly increased at 8 and 11 weeks, nicely correlated with collagen deposition, as evaluated histologically by Masson’s Trichrome staining, and airway epithelium hypertrophy, and was also partly inhibited by budesonide. In conclusion, FMT proved suitable for longitudinal study to evaluate asthma progression, both in terms of inflammatory cell infiltration and airway remodeling, allowing the determination of treatment efficacy in a chronic asthma model in mice.

Magnetic properties and Spin dynamics in magnetic Molecular Rings

Molecular nanomagnets are spin clusters whose topology and magnetic interactions can be modulated at the level of the chemical synthesis. They are formed by a small number of transition metal ions coupled by the Heisenberg's exchange interactions. Each cluster is magnetically isolated from its neighbors by organic ligands, making each unit not interacting with the others. Therefore, we can investigate the magnetic properties of an isolated molecular nanomagnet by bulk measurements. The present thesis has been mostly devoted to the experimental investigation of the magnetic properties and spin dynamics of different classes of antiferromagnetic (AF) molecular rings. This study has been exploiting various techniques of investigations, such as Nuclear Magnetic Resonance (NMR), muon spin relaxation (muSR) and SQUiD magnetometry. We investigate the magnetic properties and the phonon-induced relaxation dynamics of the first regular Cr9 antiferromagnetic (AF) ring, which represents a prototype frustrated AF ring. The magnetically-open AF rings like Cr8Cd are model systems for the study of the microscopic magnetic behaviour of finite AF Heisenberg chains. In this type of system the different magnetic behaviour depends length and on the parity of the chain (odd or even). In order to study the local spin densities on the Cr sites, the Cr-NMR spectra was collected at low temperature. The experimental result confirm the theoretical predictions for the spin configuration. Finally, the study of Dy6, the first rare-earth based ring that has been ever synthesized, has been performed by AC-SQuID and muSR measurements. We found that the dynamics is characterized by more than one characteristic correlation time, whose values depend strongly on the applied field.

Characterization of the structure of RAMP1 by mutagenesis and molecular modeling

Receptor activity modifying proteins (RAMPs) are a family of single-pass transmembrane proteins that dimerize with G-protein-coupled receptors. They may alter the ligand recognition properties of the receptors (particularly for the calcitonin receptor-like receptor, CLR). Very little structural information is available about RAMPs. Here, an ab initio model has been generated for the extracellular domain of RAMP1. The disulfide bond arrangement (Cys 27-Cys82, Cys40-Cys72, and Cys 57-Cys104) was determined by site-directed mutagenesis. The secondary structure (a-helices from residues 29-51, 60-80, and 87-100) was established from a consensus of predictive routines. Using these constraints, an assemblage of 25,000 structures was constructed and these were ranked using an all-atom statistical potential. The best 1000 conformations were energy minimized. The lowest scoring model was refined by molecular dynamics simulation. To validate our strategy, the same methods were applied to three proteins of known structure; PDB:1HP8, PDB:1V54 chain H (residues 21-85), and PDB:1T0P. When compared to the crystal structures, the models had root mean-square deviations of 3.8 Å, 4.1 Å, and 4.0 Å, respectively. The model of RAMP1 suggested that Phe93, Tyr 100, and Phe101 form a binding interface for CLR, whereas Trp74 and Phe92 may interact with ligands that bind to the CLR/RAMP1 heterodimer. © 2006 by the Biophysical Society.

Visualization of molecular fingerprints

A visualization plot of a data set of molecular data is a useful tool for gaining insight into a set of molecules. In chemoinformatics, most visualization plots are of molecular descriptors, and the statistical model most often used to produce a visualization is principal component analysis (PCA). This paper takes PCA, together with four other statistical models (NeuroScale, GTM, LTM, and LTM-LIN), and evaluates their ability to produce clustering in visualizations not of molecular descriptors but of molecular fingerprints. Two different tasks are addressed: understanding structural information (particularly combinatorial libraries) and relating structure to activity. The quality of the visualizations is compared both subjectively (by visual inspection) and objectively (with global distance comparisons and local k-nearest-neighbor predictors). On the data sets used to evaluate clustering by structure, LTM is found to perform significantly better than the other models. In particular, the clusters in LTM visualization space are consistent with the relationships between the core scaffolds that define the combinatorial sublibraries. On the data sets used to evaluate clustering by activity, LTM again gives the best performance but by a smaller margin. The results of this paper demonstrate the value of using both a nonlinear projection map and a Bernoulli noise model for modeling binary data.

Controlling protein molecular dynamics:how to accelerate folding while preserving the native state

The dynamics of peptides and proteins generated by classical molecular dynamics (MD) is described by using a Markov model. The model is built by clustering the trajectory into conformational states and estimating transition probabilities between the states. Assuming that it is possible to influence the dynamics of the system by varying simulation parameters, we show how to use the Markov model to determine the parameter values that preserve the folded state of the protein and at the same time, reduce the folding time in the simulation. We investigate this by applying the method to two systems. The first system is an imaginary peptide described by given transition probabilities with a total folding time of 1 micros. We find that only small changes in the transition probabilities are needed to accelerate (or decelerate) the folding. This implies that folding times for slowly folding peptides and proteins calculated using MD cannot be meaningfully compared to experimental results. The second system is a four residue peptide valine-proline-alanine-leucine in water. We control the dynamics of the transitions by varying the temperature and the atom masses. The simulation results show that it is possible to find the combinations of parameter values that accelerate the dynamics and at the same time preserve the native state of the peptide. A method for accelerating larger systems without performing simulations for the whole folding process is outlined.

Sensitivity of peptide conformational dynamics on clustering of a classical molecular dynamics trajectory

We investigate the sensitivity of a Markov model with states and transition probabilities obtained from clustering a molecular dynamics trajectory. We have examined a 500 ns molecular dynamics trajectory of the peptide valine-proline-alanine-leucine in explicit water. The sensitivity is quantified by varying the boundaries of the clusters and investigating the resulting variation in transition probabilities and the average transition time between states. In this way, we represent the effect of clustering using different clustering algorithms. It is found that in terms of the investigated quantities, the peptide dynamics described by the Markov model is sensitive to the clustering; in particular, the average transition times are found to vary up to 46%. Moreover, inclusion of nonphysical sparsely populated clusters can lead to serious errors of up to 814%. In the investigation, the time step used in the transition matrix is determined by the minimum time scale on which the system behaves approximately Markovian. This time step is found to be about 100 ps. It is concluded that the description of peptide dynamics with transition matrices should be performed with care, and that using standard clustering algorithms to obtain states and transition probabilities may not always produce reliable results.

Liquid-phase adsorption of n-paraffins on type 5A molecular sieves

As a basis for the commercial separation of normal paraffins a detailed study has been made of factors affecting the adsorption of binary liquid mixtures of high molecular weight normal paraffins (C12, C16, and C20) from isooctane on type 5A molecular sieves. The literature relating to molecular sieve properties and applications, and to liquid-phase adsorption of high molecular weight normal paraffin compounds by zeolites, was reviewed. Equilibrium isotherms were determined experimentally for the normal paraffins under investigation at temperatures of 303oK, 323oK and 343oK and showed a non-linear, favourable- type of isotherm. A higher equilibrium amount was adsorbed with lower molecular weight normal paraffins. An increase in adsorption temperature resulted in a decrease in the adsorption value. Kinetics of adsorption were investigated for the three normal paraffins at different temperatures. The effective diffusivity and the rate of adsorption of each normal paraffin increased with an increase in temperature in the range 303 to 343oK. The value of activation energy was between 2 and 4 kcal/mole. The dynamic properties of the three systems were investigated over a range of operating conditions (i.e. temperature, flow rate, feed concentration, and molecular sieve size in the range 0.032 x 10-3 to 2 x 10-3m) with a packed column. The heights of adsorption zones calculated by two independent equations (one based on a constant width, constant velocity and adsorption zone and the second on a solute material balance within the adsorption zone) agreed within 3% which confirmed the validity of using the mass transfer zone concept to provide a simple design procedure for the systems under study. The dynamic capacity of type 5A sieves for n-eicosane was lower than for n-hexadecane and n-dodecane corresponding to a lower equilibrium loading capacity and lower overall mass transfer coefficient. The values of individual external, internal, theoretical and experimental overall mass transfer coefficient were determined. The internal resistance was in all cases rate-controlling. A mathematical model for the prediction of dynamic breakthrough curves was developed analytically and solved from the equilibrium isotherm and the mass transfer rate equation. The experimental breakthrough curves were tested against both the proposed model and a graphical method developed by Treybal. The model produced the best fit with mean relative percent deviations of 26, 22, and 13% for the n-dodecane, n-hexadecane, and n-eicosane systems respectively.